Factors influencing work participation of adults with developmental dyslexia: a systematic review

Abstract

BackgroundEvidence has been synthesized to determine hindering and facilitating factors associated with the work participation of adults with developmental dyslexia (DD), classified according to the International Classification of Functioning, Disability and Health (ICF).MethodsA systematic literature review has been performed. Two search strings were used to determine the population and the context of work. The ICF was expanded with two subdivisions: one that made the environmental factors more work-related and a subdivision of personal factors. For data extraction the method known as qualitative metasummary was used and the manifest frequency effect size (MFES) for each category in the ICF was calculated.ResultsFrom 33 included studies 318 factors have been extracted and classified in the ICF. In the classification the frequency of occurrences and the consistency in direction (i.e., hindering or facilitating) have been made visible. The ICF categories with the highest MFES were mental functions with factors like feelings and emotions about dyslexia; activities like reading or writing/spelling; participation with factors like acquiring and keeping a job; social relationships at work where the attitudes and support of the employer and co-workers are important; working conditions with factors like the availability of assistive technology and accommodations on the job; and personal factors like self-disclosure and coping strategies.ConclusionsIn the context of work DD affects nearly all domains of functioning, mostly in a negative way. Within each domain the impact of DD increases over the course of life. To overcome that negative influence, many forms of adaptation, compensation, or coping are mentioned. Also notable is the lack of positive attitudes toward DD of the participants with DD—with the exception of the attitudes of teachers with DD—as well as on the part of colleagues, supervisors, and employers.

Remapping the cognitive and neural profiles of children who struggle at school

“…In the UK for example, around 30% of the school population fail to meet expected targets in reading or maths at age 11 (Department for Education United Kingdom, ). The long‐term outcomes for children who struggle at school include continued educational underachievement, poor mental health (Roeser & Eccles, ), and underemployment (Bynner & Parsons, ; de Beer, Engels, Heerkens, & van der Klink, ).…”

The relationship between emotional experience with dyslexia and work self‐efficacy among adults with dyslexia

“…These emotions often follow AWD into adulthood (Nalavany, Carwan, & Rennick, 2011;Hellendoorn & Ruijssenaars, 2000;McNulty, 2003). De Beer et al (2014) found in their seminal research that risk and protective factors influence work participation of AWD. It is not surprising that emotions about having dyslexia were one of the most frequently mentioned work-related factors cited throughout the extant research.…”

“…Such experiences can heighten the global anxiety that is already a part of the emotional challenge that often accompanies dyslexia/ learning disability. In their systematic review of the literature, de Beer et al (2014) found that negative emotions from dyslexia were frequently voiced among the participants when reflecting upon their working lives. This finding is compelling as persistent literacy issues, keeping a job, and mostly negative emotions about dyslexia were mentioned most often in this comprehensive work.…”

Designing a Computerized Neuro-Cognitive Program for Early Diagnosing Children at Risk for Dyslexia

“…However, our program assesses some of the important cognitive abilities required for reading ability, besides its suitable format and accuracy (the value of 46.19 and 19.58 for auditory and visual working memories), which were both significant in distinguishing and the amount of 0.55 in differentiation in according to rapid naming task. Stanford-Binet Intelligence scale is another instance which was applied in learning disabilities prediction [31], besides estimating IQ. The previously mentioned hints are consistent in this example too.…”